Overview

Dataset statistics

Number of variables10
Number of observations106
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.7 KiB
Average record size in memory84.2 B

Variable types

Numeric3
Categorical3
Text3
DateTime1

Dataset

Description울산광역시 시 및 지자체(구군) 주택건설사업계획 승인 정보를 제공하고 있습니다.(사업주체명, 사업대지, 세대수, 층수, 동수, 착공여부 등)
URLhttps://www.data.go.kr/data/15091231/fileData.do

Alerts

연번 is highly overall correlated with 구분High correlation
연면적 is highly overall correlated with 세대수High correlation
세대수 is highly overall correlated with 연면적High correlation
구분 is highly overall correlated with 연번High correlation
착공여부 is highly overall correlated with 비고High correlation
비고 is highly overall correlated with 착공여부High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 01:46:29.913369
Analysis finished2023-12-12 01:46:32.193380
Duration2.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct106
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53.5
Minimum1
Maximum106
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T10:46:32.270608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.25
Q127.25
median53.5
Q379.75
95-th percentile100.75
Maximum106
Range105
Interquartile range (IQR)52.5

Descriptive statistics

Standard deviation30.743563
Coefficient of variation (CV)0.57464604
Kurtosis-1.2
Mean53.5
Median Absolute Deviation (MAD)26.5
Skewness0
Sum5671
Variance945.16667
MonotonicityStrictly increasing
2023-12-12T10:46:32.419411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
81 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
76 1
 
0.9%
75 1
 
0.9%
74 1
 
0.9%
73 1
 
0.9%
72 1
 
0.9%
Other values (96) 96
90.6%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
102 1
0.9%
101 1
0.9%
100 1
0.9%
99 1
0.9%
98 1
0.9%
97 1
0.9%

구분
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size980.0 B
남구
50 
중구
19 
울주군
15 
북구
13 
경제자유구역청
 
5

Length

Max length7
Median length2
Mean length2.3773585
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중구
2nd row중구
3rd row중구
4th row중구
5th row중구

Common Values

ValueCountFrequency (%)
남구 50
47.2%
중구 19
 
17.9%
울주군 15
 
14.2%
북구 13
 
12.3%
경제자유구역청 5
 
4.7%
동구 4
 
3.8%

Length

2023-12-12T10:46:32.551699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:46:32.665377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남구 50
47.2%
중구 19
 
17.9%
울주군 15
 
14.2%
북구 13
 
12.3%
경제자유구역청 5
 
4.7%
동구 4
 
3.8%

사업명_사업주체
Text

Distinct90
Distinct (%)84.9%
Missing0
Missing (%)0.0%
Memory size980.0 B
2023-12-12T10:46:32.884530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length19
Mean length11.301887
Min length5

Characters and Unicode

Total characters1198
Distinct characters204
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)75.5%

Sample

1st row우정동뉴시티지역주택조합
2nd row학성동지역주택조합
3rd row울산우정동지역주택조합
4th row우리자산신탁㈜[당초(주)정선프라임]
5th row신한자산신탁㈜[당초 에이치아이(주)]
ValueCountFrequency (%)
교보자산신탁(주 5
 
3.1%
문수로 5
 
3.1%
코리아신탁(주 4
 
2.5%
울산역 4
 
2.5%
율동피에프브이(주 3
 
1.9%
힐스테이트 3
 
1.9%
지역주택조합 2
 
1.2%
에일린의뜰 2
 
1.2%
덕하지구 2
 
1.2%
㈜하나자산신탁 2
 
1.2%
Other values (114) 128
80.0%
2023-12-12T10:46:33.344850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 60
 
5.0%
56
 
4.7%
( 42
 
3.5%
) 42
 
3.5%
㈜ 40
 
3.3%
산 35
 
2.9%
신 35
 
2.9%
지 28
 
2.3%
이 28
 
2.3%
탁 27
 
2.3%
Other values (194) 805
67.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 964
80.5%
Space Separator 56
 
4.7%
Open Punctuation 51
 
4.3%
Close Punctuation 51
 
4.3%
Other Symbol 40
 
3.3%
Decimal Number 15
 
1.3%
Uppercase Letter 13
 
1.1%
Dash Punctuation 6
 
0.5%
Math Symbol 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 60
 
6.2%
산 35
 
3.6%
신 35
 
3.6%
지 28
 
2.9%
이 28
 
2.9%
탁 27
 
2.8%
스 27
 
2.8%
택 24
 
2.5%
합 22
 
2.3%
리 22
 
2.3%
Other values (175) 656
68.0%
Decimal Number
ValueCountFrequency (%)
1 4
26.7%
2 4
26.7%
0 3
20.0%
4 2
13.3%
8 1
 
6.7%
5 1
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
B 8
61.5%
L 2
 
15.4%
C 2
 
15.4%
K 1
 
7.7%
Open Punctuation
ValueCountFrequency (%)
( 42
82.4%
[ 9
 
17.6%
Close Punctuation
ValueCountFrequency (%)
) 42
82.4%
] 9
 
17.6%
Space Separator
ValueCountFrequency (%)
56
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 40
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Math Symbol
ValueCountFrequency (%)
→ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1004
83.8%
Common 181
 
15.1%
Latin 13
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 60
 
6.0%
㈜ 40
 
4.0%
산 35
 
3.5%
신 35
 
3.5%
지 28
 
2.8%
이 28
 
2.8%
탁 27
 
2.7%
스 27
 
2.7%
택 24
 
2.4%
합 22
 
2.2%
Other values (176) 678
67.5%
Common
ValueCountFrequency (%)
56
30.9%
( 42
23.2%
) 42
23.2%
] 9
 
5.0%
[ 9
 
5.0%
- 6
 
3.3%
1 4
 
2.2%
2 4
 
2.2%
0 3
 
1.7%
4 2
 
1.1%
Other values (4) 4
 
2.2%
Latin
ValueCountFrequency (%)
B 8
61.5%
L 2
 
15.4%
C 2
 
15.4%
K 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 964
80.5%
ASCII 193
 
16.1%
None 40
 
3.3%
Arrows 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 60
 
6.2%
산 35
 
3.6%
신 35
 
3.6%
지 28
 
2.9%
이 28
 
2.9%
탁 27
 
2.8%
스 27
 
2.8%
택 24
 
2.5%
합 22
 
2.3%
리 22
 
2.3%
Other values (175) 656
68.0%
ASCII
ValueCountFrequency (%)
56
29.0%
( 42
21.8%
) 42
21.8%
] 9
 
4.7%
[ 9
 
4.7%
B 8
 
4.1%
- 6
 
3.1%
1 4
 
2.1%
2 4
 
2.1%
0 3
 
1.6%
Other values (7) 10
 
5.2%
None
ValueCountFrequency (%)
㈜ 40
100.0%
Arrows
ValueCountFrequency (%)
→ 1
100.0%

대지위치
Text

Distinct105
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size980.0 B
2023-12-12T10:46:33.767154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length11.349057
Min length6

Characters and Unicode

Total characters1203
Distinct characters92
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique104 ?
Unique (%)98.1%

Sample

1st row우정동 272-2 번지 일원
2nd row학성동 397-1 번지 일원
3rd row우정동 274-85번지 일원
4th row반구동 554-5번지 일원
5th row학산동 167-4번지 일원
ValueCountFrequency (%)
일원 23
 
8.8%
신정동 22
 
8.5%
야음동 14
 
5.4%
우정동 8
 
3.1%
삼남면 7
 
2.7%
삼산동 6
 
2.3%
무거동 4
 
1.5%
신화리 4
 
1.5%
신천동 4
 
1.5%
복산동 3
 
1.2%
Other values (150) 165
63.5%
2023-12-12T10:46:34.383751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
160
 
13.3%
1 95
 
7.9%
동 88
 
7.3%
- 87
 
7.2%
2 59
 
4.9%
5 45
 
3.7%
3 42
 
3.5%
6 36
 
3.0%
4 35
 
2.9%
지 34
 
2.8%
Other values (82) 522
43.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 510
42.4%
Decimal Number 417
34.7%
Space Separator 160
 
13.3%
Dash Punctuation 87
 
7.2%
Uppercase Letter 19
 
1.6%
Open Punctuation 5
 
0.4%
Close Punctuation 5
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 88
17.3%
지 34
 
6.7%
정 30
 
5.9%
신 30
 
5.9%
일 26
 
5.1%
원 24
 
4.7%
번 20
 
3.9%
음 14
 
2.7%
산 14
 
2.7%
삼 14
 
2.7%
Other values (64) 216
42.4%
Decimal Number
ValueCountFrequency (%)
1 95
22.8%
2 59
14.1%
5 45
10.8%
3 42
10.1%
6 36
 
8.6%
4 35
 
8.4%
8 31
 
7.4%
7 31
 
7.4%
0 22
 
5.3%
9 21
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
B 11
57.9%
L 5
26.3%
C 2
 
10.5%
A 1
 
5.3%
Space Separator
ValueCountFrequency (%)
160
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 87
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 674
56.0%
Hangul 510
42.4%
Latin 19
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 88
17.3%
지 34
 
6.7%
정 30
 
5.9%
신 30
 
5.9%
일 26
 
5.1%
원 24
 
4.7%
번 20
 
3.9%
음 14
 
2.7%
산 14
 
2.7%
삼 14
 
2.7%
Other values (64) 216
42.4%
Common
ValueCountFrequency (%)
160
23.7%
1 95
14.1%
- 87
12.9%
2 59
 
8.8%
5 45
 
6.7%
3 42
 
6.2%
6 36
 
5.3%
4 35
 
5.2%
8 31
 
4.6%
7 31
 
4.6%
Other values (4) 53
 
7.9%
Latin
ValueCountFrequency (%)
B 11
57.9%
L 5
26.3%
C 2
 
10.5%
A 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 693
57.6%
Hangul 510
42.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
160
23.1%
1 95
13.7%
- 87
12.6%
2 59
 
8.5%
5 45
 
6.5%
3 42
 
6.1%
6 36
 
5.2%
4 35
 
5.1%
8 31
 
4.5%
7 31
 
4.5%
Other values (8) 72
10.4%
Hangul
ValueCountFrequency (%)
동 88
17.3%
지 34
 
6.7%
정 30
 
5.9%
신 30
 
5.9%
일 26
 
5.1%
원 24
 
4.7%
번 20
 
3.9%
음 14
 
2.7%
산 14
 
2.7%
삼 14
 
2.7%
Other values (64) 216
42.4%

연면적
Real number (ℝ)

HIGH CORRELATION 

Distinct105
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean86319.517
Minimum38.746
Maximum804031
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T10:46:34.574704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum38.746
5-th percentile8750
Q141023
median64557.5
Q3103240.5
95-th percentile249175.25
Maximum804031
Range803992.25
Interquartile range (IQR)62217.5

Descriptive statistics

Standard deviation96630.094
Coefficient of variation (CV)1.1194466
Kurtosis29.37214
Mean86319.517
Median Absolute Deviation (MAD)29084
Skewness4.563991
Sum9149868.8
Variance9.337375 × 109
MonotonicityNot monotonic
2023-12-12T10:46:34.737685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
283136.0 2
 
1.9%
80331.0 1
 
0.9%
50115.87 1
 
0.9%
33921.0 1
 
0.9%
117820.0 1
 
0.9%
38855.0 1
 
0.9%
43721.0 1
 
0.9%
82179.0 1
 
0.9%
94978.0 1
 
0.9%
15053.0 1
 
0.9%
Other values (95) 95
89.6%
ValueCountFrequency (%)
38.746 1
0.9%
1983.0 1
0.9%
2831.0 1
0.9%
3480.2 1
0.9%
6361.0 1
0.9%
8419.0 1
0.9%
9743.0 1
0.9%
12063.48 1
0.9%
15053.0 1
0.9%
17101.0 1
0.9%
ValueCountFrequency (%)
804031.0 1
0.9%
383788.0 1
0.9%
298386.0 1
0.9%
283136.0 2
1.9%
253309.0 1
0.9%
236774.0 1
0.9%
232633.0 1
0.9%
173667.0 1
0.9%
140387.0 1
0.9%
137708.0 1
0.9%

층수_동수
Text

Distinct82
Distinct (%)77.4%
Missing0
Missing (%)0.0%
Memory size980.0 B
2023-12-12T10:46:35.374894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0566038
Min length5

Characters and Unicode

Total characters642
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)60.4%

Sample

1st row29층_5동
2nd row21층_13동
3rd row29층_5동
4th row29층_동
5th row49층_3동
ValueCountFrequency (%)
29층_3동 4
 
3.8%
39층_2동 3
 
2.8%
35층_2동 3
 
2.8%
49층_3동 3
 
2.8%
27층_2동 3
 
2.8%
41층_2동 2
 
1.9%
45층_3동 2
 
1.9%
29층_2동 2
 
1.9%
37층_4동 2
 
1.9%
29층_5동 2
 
1.9%
Other values (72) 80
75.5%
2023-12-12T10:46:35.929523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
층 106
16.5%
_ 106
16.5%
동 106
16.5%
2 80
12.5%
4 47
7.3%
3 46
7.2%
1 36
 
5.6%
9 34
 
5.3%
5 30
 
4.7%
7 15
 
2.3%
Other values (3) 36
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 324
50.5%
Other Letter 212
33.0%
Connector Punctuation 106
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 80
24.7%
4 47
14.5%
3 46
14.2%
1 36
11.1%
9 34
10.5%
5 30
 
9.3%
7 15
 
4.6%
6 15
 
4.6%
8 11
 
3.4%
0 10
 
3.1%
Other Letter
ValueCountFrequency (%)
층 106
50.0%
동 106
50.0%
Connector Punctuation
ValueCountFrequency (%)
_ 106
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 430
67.0%
Hangul 212
33.0%

Most frequent character per script

Common
ValueCountFrequency (%)
_ 106
24.7%
2 80
18.6%
4 47
10.9%
3 46
10.7%
1 36
 
8.4%
9 34
 
7.9%
5 30
 
7.0%
7 15
 
3.5%
6 15
 
3.5%
8 11
 
2.6%
Hangul
ValueCountFrequency (%)
층 106
50.0%
동 106
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 430
67.0%
Hangul 212
33.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
층 106
50.0%
동 106
50.0%
ASCII
ValueCountFrequency (%)
_ 106
24.7%
2 80
18.6%
4 47
10.9%
3 46
10.7%
1 36
 
8.4%
9 34
 
7.9%
5 30
 
7.0%
7 15
 
3.5%
6 15
 
3.5%
8 11
 
2.6%

세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct97
Distinct (%)91.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean455.01887
Minimum30
Maximum4080
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T10:46:36.119519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile81.5
Q1182.75
median341.5
Q3498.25
95-th percentile937.25
Maximum4080
Range4050
Interquartile range (IQR)315.5

Descriptive statistics

Standard deviation517.36328
Coefficient of variation (CV)1.137015
Kurtosis25.609692
Mean455.01887
Median Absolute Deviation (MAD)159.5
Skewness4.4336554
Sum48232
Variance267664.76
MonotonicityNot monotonic
2023-12-12T10:46:36.290879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193 3
 
2.8%
436 2
 
1.9%
303 2
 
1.9%
301 2
 
1.9%
400 2
 
1.9%
803 2
 
1.9%
848 2
 
1.9%
168 2
 
1.9%
116 1
 
0.9%
264 1
 
0.9%
Other values (87) 87
82.1%
ValueCountFrequency (%)
30 1
0.9%
38 1
0.9%
58 1
0.9%
75 1
0.9%
77 1
0.9%
79 1
0.9%
89 1
0.9%
108 1
0.9%
109 1
0.9%
116 1
0.9%
ValueCountFrequency (%)
4080 1
0.9%
2625 1
0.9%
2033 1
0.9%
1529 1
0.9%
1430 1
0.9%
967 1
0.9%
848 2
1.9%
817 1
0.9%
803 2
1.9%
788 1
0.9%

승인일자
Date

Distinct94
Distinct (%)88.7%
Missing0
Missing (%)0.0%
Memory size980.0 B
Minimum2007-11-02 00:00:00
Maximum2023-10-20 00:00:00
2023-12-12T10:46:36.452340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:46:36.654106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

착공여부
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size980.0 B
미착공
56 
착공
50 

Length

Max length3
Median length3
Mean length2.5283019
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row착공
2nd row미착공
3rd row미착공
4th row착공
5th row미착공

Common Values

ValueCountFrequency (%)
미착공 56
52.8%
착공 50
47.2%

Length

2023-12-12T10:46:36.903911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:46:37.094796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미착공 56
52.8%
착공 50
47.2%

비고
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size980.0 B
없음
64 
공사중
26 
공사중단
 
5
동별사용검사
 
3
분양취소
 
3
Other values (5)
 
5

Length

Max length6
Median length2
Mean length2.6698113
Min length2

Unique

Unique5 ?
Unique (%)4.7%

Sample

1st row없음
2nd row없음
3rd row없음
4th row없음
5th row없음

Common Values

ValueCountFrequency (%)
없음 64
60.4%
공사중 26
24.5%
공사중단 5
 
4.7%
동별사용검사 3
 
2.8%
분양취소 3
 
2.8%
임시사용검사 1
 
0.9%
사용검사완료 1
 
0.9%
임시사용승인 1
 
0.9%
공사중,분양 1
 
0.9%
미분양 1
 
0.9%

Length

2023-12-12T10:46:37.312437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:46:37.564317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
없음 64
60.4%
공사중 26
24.5%
공사중단 5
 
4.7%
동별사용검사 3
 
2.8%
분양취소 3
 
2.8%
임시사용검사 1
 
0.9%
사용검사완료 1
 
0.9%
임시사용승인 1
 
0.9%
공사중,분양 1
 
0.9%
미분양 1
 
0.9%

Interactions

2023-12-12T10:46:31.603492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:46:30.959901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:46:31.299282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:46:31.724875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:46:31.071266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:46:31.396301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:46:31.861484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:46:31.189038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:46:31.497761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:46:37.733183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분사업명_사업주체연면적층수_동수세대수승인일자착공여부비고
연번1.0000.9170.9320.3410.8520.4110.9870.5690.583
구분0.9171.0001.0000.5050.9820.2310.9900.2300.516
사업명_사업주체0.9321.0001.0001.0000.9700.9970.9940.8201.000
연면적0.3410.5051.0001.0000.9930.8830.9620.0000.000
층수_동수0.8520.9820.9700.9931.0000.9870.9540.0000.946
세대수0.4110.2310.9970.8830.9871.0000.9680.1520.000
승인일자0.9870.9900.9940.9620.9540.9681.0000.9410.992
착공여부0.5690.2300.8200.0000.0000.1520.9411.0000.967
비고0.5830.5161.0000.0000.9460.0000.9920.9671.000
2023-12-12T10:46:37.953133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
착공여부구분비고
착공여부1.0000.1610.810
구분0.1611.0000.295
비고0.8100.2951.000
2023-12-12T10:46:38.142861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번연면적세대수구분착공여부비고
연번1.000-0.017-0.0710.7720.4030.210
연면적-0.0171.0000.9250.2010.0000.000
세대수-0.0710.9251.0000.1370.1570.000
구분0.7720.2010.1371.0000.1610.295
착공여부0.4030.0000.1570.1611.0000.810
비고0.2100.0000.0000.2950.8101.000

Missing values

2023-12-12T10:46:31.984710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:46:32.139836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

연번구분사업명_사업주체대지위치연면적층수_동수세대수승인일자착공여부비고
01중구우정동뉴시티지역주택조합우정동 272-2 번지 일원80331.029층_5동5312021-11-29착공없음
12중구학성동지역주택조합학성동 397-1 번지 일원140387.021층_13동7882021-12-17미착공없음
23중구울산우정동지역주택조합우정동 274-85번지 일원88447.029층_5동5332022-02-28미착공없음
34중구우리자산신탁㈜[당초(주)정선프라임]반구동 554-5번지 일원118036.029층_동6752022-03-21착공없음
45중구신한자산신탁㈜[당초 에이치아이(주)]학산동 167-4번지 일원128329.049층_3동6342022-05-26미착공없음
56중구울산다운2지구 공공지원민간임대주택(우미건설(주))울산다운2 공공주택지구 B-3BL108553.024층_12동6522022-12-12미착공없음
67중구우정지역주택조합[태화강유보라]우정동 286-7 외 19필지92405.049층_5동4552018-06-29착공공사중
78중구우정리버힐스지역주택조합우정동 187-3외 33필지63330.049층_3동3122019-06-17착공공사중
89중구다운지역주택조합다운동 741-2 외 51필지51753.018층_6동4002020-03-19착공공사중
910중구B-04주택재개발교동 190-4 일원804031.029층_55동40802018-11-26미착공없음
연번구분사업명_사업주체대지위치연면적층수_동수세대수승인일자착공여부비고
9697울주군발리지역주택조합(한양립스)온양 발리 523-153897.029층_6동4422018-05-25착공공사중
9798울주군통도지역주택조합(방기리아크리티)삼남면 방기리 962-16361.015층_1동582018-10-24착공공사중단
9899울주군㈜지음디앤시온양읍 대안리 269-1번지 일원9743.020층_1동752019-11-22착공공사중
99100울주군금아건설주식회사(가천 더 하우스)삼남면 가천리 산20-12831.04층_2동302020-04-21미착공없음
100101울주군㈜제이케이홀딩스삼남읍 교동리 355-2 일원84947.045층_3동4002022-09-27미착공없음
101102경제자유구역청동문굿모닝힐2차 대동종합건설㈜삼남면 교동리 1679-1번지232633.040층_7동6302018-04-04미착공없음
102103경제자유구역청울산역 우방 아이유쉘 [(주)우방]삼남면 신화리 1601-2103327.026층_4동3442021-11-11착공공사중
103104경제자유구역청울산역 역세권 주상복합 (무궁화신탁)삼남면 신화리 1608-4126054.012층_5동2482021-12-31미착공없음
104105경제자유구역청울산역 힐스테이트 신일산업개발㈜삼남면 신화리 45283136.040층_5동4362022-10-24미착공없음
105106경제자유구역청울산역 역세권 주상복합 에스아이개발㈜삼남면 신화리 45283136.039층_7동7562023-04-04미착공없음